Network analysis of anxiety and depressive symptoms during the COVID-19 pandemic in older adults in the United Kingdom

被引：7
作者：
Ramos-Vera C. [1 ]
García O’Diana A. [1 ]
Basauri-Delgado M. [2 ]
Calizaya-Milla Y.E. [3 ]
Saintila J. [4 ]
机构：
[1] Área de Investigación, Universidad César Vallejo, Lima
[2] Doctorando en Psicología, Universidad Femenina del Sagrado Corazón (UNIFE), Lima
[3] Facultad de Ciencias de la Salud, Universidad Peruana Unión, Chosica
[4] Escuela de Medicina Humana, Facultad de Ciencias de la Salud, Universidad Señor de Sipán, Chiclayo
来源：
Scientific Reports | / 14卷 / 1期
关键词：
Anxiety; Cross-lagged panel network; Depression; Network analysis; Older adult;
D O I：
10.1038/s41598-024-58256-8
中图分类号：
学科分类号：
摘要：
The health crisis caused by COVID-19 in the United Kingdom and the confinement measures that were subsequently implemented had unprecedented effects on the mental health of older adults, leading to the emergence and exacerbation of different comorbid symptoms including depression and anxiety. This study examined and compared depression and anxiety symptom networks in two specific quarantine periods (June–July and November–December) in the older adult population in the United Kingdom. We used the database of the English Longitudinal Study of Aging COVID-19 Substudy, consisting of 5797 participants in the first stage (54% women) and 6512 participants in the second stage (56% women), all over 50 years of age. The symptoms with the highest centrality in both times were: “Nervousness (A1)” and “Inability to relax (A4)” in expected influence and predictability, and “depressed mood (D1”; bridging expected influence). The latter measure along with "Irritability (A6)" overlapped in both depression and anxiety clusters in both networks. In addition, a the cross-lagged panel network model was examined in which a more significant influence on the direction of the symptom "Nervousness (A1)" by the depressive symptoms of "Anhedonia (D6)", "Hopelessness (D7)", and "Sleep problems (D3)" was observed; the latter measure has the highest predictive capability of the network. The results report which symptoms had a higher degree of centrality and transdiagnostic overlap in the cross-sectional networks (invariants) and the cross-lagged panel network model of anxious and depressive symptomatology. © The Author(s) 2024.
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